The present invention relates to a spindle device for operating a production machine. The present invention further relates to a monitoring system for monitoring at least one such spindle device, as well as to a method of operating a spindle device.
Nothing in the following discussion of the state of the art is to be construed as an admission of prior art.
Increase in productivity is a primary goal for the manufacturing industry and the stimulus for optimization and development in the field of production planning and process technique. It is therefore of great importance to operate a primary spindle as effective as possible for a production machine, e.g. a milling machine or a lathe. To enhance and ensure a high effectiveness, the need for an automated supervision of the primary spindle is desired.
For monitoring spindles effectively, existing systems provide a classification of various conditions of the spindle, i.e. establishment of limit values for measured, processed and recorded signals or information. Currently available diagnosis systems are based on the evaluation of a single vibration signal which is ascertained by a vibration sensor mounted externally to the spindle. The spindle diagnosis takes place almost in real time during periodic sensor measurement. Generated information remains hereby with the owner of the spindle. Machine manufacturers or spindle manufacturers normally do not have access to the recorded data.
State evaluation is typically realized by means of a trend analysis of parameters obtained from a measuring signal, such as for example the effective value of the acceleration or the vibration speed across certain frequency ranges or amplitude spectrums. The principle of trend analysis during a periodic data acquisition is illustrated in FIG. 1 which is a graphical illustration of the vibration amplitude of a bearing of a primary spindle as a function of the date or time. So long as the vibration amplitude in the present example of FIG. 1 is smaller than 50 amplitude units, the vibration amplitude is in a non-critical range 1 which represents a state in which the spindle and thus the machine operates properly. In range 2 above the range 1, the vibration amplitude of the spindle bearing is between 50 and 80 amplitude units, and the spindle and thus the machine are in a state in which maintenance works needs to be scheduled and a breakdown can be expected. When the vibrations are even higher and reach the range 3 above 80 amplitude units, the spindle and thus the machine are in a state that requires immediate actions as a breakdown is imminent.
The graph 4 shown in FIG. 1 represents a typical profile of the vibration amplitude of the bearing of a primary spindle as a function of the time (date). Starting from an actual time instance 5, a time instance 7 can be predicted through extrapolation 6 when the machine breaks down or actions are absolutely required. The time period up to the time instance 7 may thus be exploited to undertake the needed maintenance works. The limit values required for delineating the various states are ascertained through statistically obtained data. This learning process is time-consuming and produces a limit value for only a single spindle type in a particular machine and possibly for only a single particular manufacturing operation. This type of limit value determination is thus unsuitable for operation of primary spindles and other production machines.
It would therefore be desirable and advantageous to provide an improved diagnosis system for spindle devices, which obviates prior art shortcomings and which is simple in structure and yet reliable in operation.